Notes on Features. Ling 571 Deep Techniques for NLP February 10, 2014

Size: px
Start display at page:

Download "Notes on Features. Ling 571 Deep Techniques for NLP February 10, 2014"

Transcription

1 Notes on Features Ling 571 Deep Techniques for NLP February 10, 2014

2 Feature Grammar in NLTK NLTK supports feature-based grammars Includes ways of associating features with CFG rules Includes readers for feature grammars.fcfg files Includes parsers Nltk.parse.FeatureEarleyChartParser

3 Feature Structures >>> fs1 = nltk.featstruct( [NUM= pl ] ) >>> print fs1 [NUM= pl ] >>> print fs1[ NUM ] pl More complex structure >>> fs2 = nltk.featstruct( [POS= N, AGR=[NUM= pl,per=3]] )

4 Reentrant Feature Structures First instance Parenthesized integer: (1) Subsequent instances: Pointer : -> (1) >>> print nltk.featstruct("[a='a', B=(1)[C='c'], D->(1)] [ A = a ] [ B = (1) [ C = c ]] [ D -> (1) ]

5 Augmenting Grammars Attach feature information to non-terminals, on N[AGR=[NUM='pl']] -> 'students N[AGR=[NUM= sg']] -> 'student So far, all values are literal or reentrant Variables allow generalization:?a Allows underspecification, e.g. Det[GEN=?a] NP[AGR=?a] -> Det[AGR=?a] N[AGR=?a]

6 Mechanics >>> fs3 = nltk.featstruct(num= pl,per=3) >>> fs4 = nltk.featstruct(num= pl ) >>> print fs4.unify(fs3) [NUM = pl ] [PER = 3 ]

7 Morphosyntactic Features Grammatical feature that influences morphological or syntactic behavior English: Number: Dog, dogs Person: Am; are; is Case: I me; he him; etc Countability:

8 Semantic Features Grammatical features that influence semantic(meaning) behavior of associated units E.g.:

9 Semantic Features Grammatical features that influence semantic(meaning) behavior of associated units E.g.:?The rocks slept.

10 Semantic Features Grammatical features that influence semantic(meaning) behavior of associated units E.g.:?The rocks slept.?colorless green ideas sleep furiously.

11 Semantic Features Many proposed: Animacy: +/- Natural gender: masculine, feminine, neuter Human: +/- Adult: +/- Liquid: +/- Etc. The milk spilled.?the cat spilled.

12 Examples The climber hiked for six hours. The climber hiked on Saturday. The climber reached the summit on Saturday. *The climber reached the summit for six hours. Contrast:

13 Examples The climber hiked for six hours. The climber hiked on Saturday. The climber reached the summit on Saturday. *The climber reached the summit for six hours. Contrast: Achievement vs activity

14 Semantic features & Parsing Can filter some classes of ambiguity Old men and women slept. (Old men) and (women) slept. (Old (men and women)) slept. Sleeping people and books lie flat. (Sleeping people) and (books) lie flat. (Sleeping (people and books ))lie flat.

15 Semantic features & Parsing Can filter some classes of ambiguity Old men and women slept. (Old men) and (women) slept. (Old (men and women)) slept. Sleeping people and books lie flat. (Sleeping people) and (books) lie flat. *(Sleeping (people and books ))lie flat.

16 Summary Features Enable compact representation of grammatical constraints Capture basic linguistic patterns Unification Creates and maintains consistency over features Integration with parsing allows filtering of illformed analyses

17 More Complex German Subject singular, masc der Hund The dog Example Subject plural, masc die Hunde The dogs

18 More Complex German Example Objects determined by verb Dative singular, masc dem Hund The dog Accusative plural, masc die Hunde The dogs

19 Contrast Subject: Die Katze The cat Subject: plural Die Katzen The cats

20 Contrast Object: Die Katze The cat Object: Der Katze The cat

21 Analysis What are the key contrasts? Number Singular, plural Gender Masc, Fem,. Case: Subject (nom), dative, accusative,. + Interactions

22 Feature Interaction Interactions of German case, number, gender Case Masc Fem Neut PL Nom Der Die Das Die Gen Des Der Des Den Dat Dem Der Dem Den Acc Den Die Das Die

23 Examples of Interaction Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Den The.Acc.Masc.sg Hund Dog.3.Masc.sg

24 Examples of Interaction Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Den The.Acc.Masc.sg Hund Dog.3.Masc.sg *Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Dem The.Dat.Masc.sg Hund Dog.3.Masc.sg

25 Examples of Interaction Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Den The.Acc.Masc.sg Hund Dog.3.Masc.sg *Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Dem The.Dat.Masc.sg Hund Dog.3.Masc.sg Die The.Nom.Fem.sg The cat helps the dog Katze Cat.3.FEM.SG hilft help.3.sg Dem The.Dat.Masc.sg Hund Dog.3.Masc.sg

26 Examples of Interaction Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Den The.Acc.Masc.sg Hund Dog.3.Masc.sg *Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG Sieht See.3.sg Dem The.Dat.Masc.sg Hund Dog.3.Masc.sg Die The.Nom.Fem.sg The cat helps the dog Katze Cat.3.FEM.SG hilft help.3.sg Dem The.Dat.Masc.sg Hund Dog.3.Masc.sg *Die The.Nom.Fem.sg The cat sees the dog Katze Cat.3.FEM.SG hilft help.3.sg Dem The.Acc.Masc.sg Hund Dog.3.Masc.sg German verbs in, at least, 2 classes: assign diff t object case

Chapter 4: Valence & Agreement CSLI Publications

Chapter 4: Valence & Agreement CSLI Publications Chapter 4: Valence & Agreement Reminder: Where We Are Simple CFG doesn t allow us to cross-classify categories, e.g., verbs can be grouped by transitivity (deny vs. disappear) or by number (deny vs. denies).

More information

An Interactive Intelligent Language Tutor Over The Internet

An Interactive Intelligent Language Tutor Over The Internet An Interactive Intelligent Language Tutor Over The Internet Trude Heift Linguistics Department and Language Learning Centre Simon Fraser University, B.C. Canada V5A1S6 E-mail: heift@sfu.ca Abstract: This

More information

Feature-Based Grammar

Feature-Based Grammar 8 Feature-Based Grammar James P. Blevins 8.1 Introduction This chapter considers some of the basic ideas about language and linguistic analysis that define the family of feature-based grammars. Underlying

More information

CS 598 Natural Language Processing

CS 598 Natural Language Processing CS 598 Natural Language Processing Natural language is everywhere Natural language is everywhere Natural language is everywhere Natural language is everywhere!"#$%&'&()*+,-./012 34*5665756638/9:;< =>?@ABCDEFGHIJ5KL@

More information

Indeterminacy by Underspecification Mary Dalrymple (Oxford), Tracy Holloway King (PARC) and Louisa Sadler (Essex) (9) was: ( case) = nom ( case) = acc

Indeterminacy by Underspecification Mary Dalrymple (Oxford), Tracy Holloway King (PARC) and Louisa Sadler (Essex) (9) was: ( case) = nom ( case) = acc Indeterminacy by Underspecification Mary Dalrymple (Oxford), Tracy Holloway King (PARC) and Louisa Sadler (Essex) 1 Ambiguity vs Indeterminacy The simple view is that agreement features have atomic values,

More information

Underlying and Surface Grammatical Relations in Greek consider

Underlying and Surface Grammatical Relations in Greek consider 0 Underlying and Surface Grammatical Relations in Greek consider Sentences Brian D. Joseph The Ohio State University Abbreviated Title Grammatical Relations in Greek consider Sentences Brian D. Joseph

More information

Introduction to HPSG. Introduction. Historical Overview. The HPSG architecture. Signature. Linguistic Objects. Descriptions.

Introduction to HPSG. Introduction. Historical Overview. The HPSG architecture. Signature. Linguistic Objects. Descriptions. to as a linguistic theory to to a member of the family of linguistic frameworks that are called generative grammars a grammar which is formalized to a high degree and thus makes exact predictions about

More information

Basic Parsing with Context-Free Grammars. Some slides adapted from Julia Hirschberg and Dan Jurafsky 1

Basic Parsing with Context-Free Grammars. Some slides adapted from Julia Hirschberg and Dan Jurafsky 1 Basic Parsing with Context-Free Grammars Some slides adapted from Julia Hirschberg and Dan Jurafsky 1 Announcements HW 2 to go out today. Next Tuesday most important for background to assignment Sign up

More information

Case government vs Case agreement: modelling Modern Greek case attraction phenomena in LFG

Case government vs Case agreement: modelling Modern Greek case attraction phenomena in LFG Case government vs Case agreement: modelling Modern Greek case attraction phenomena in LFG Dr. Kakia Chatsiou, University of Essex achats at essex.ac.uk Explorations in Syntactic Government and Subcategorisation,

More information

Natural Language Processing. George Konidaris

Natural Language Processing. George Konidaris Natural Language Processing George Konidaris gdk@cs.brown.edu Fall 2017 Natural Language Processing Understanding spoken/written sentences in a natural language. Major area of research in AI. Why? Humans

More information

Developing a TT-MCTAG for German with an RCG-based Parser

Developing a TT-MCTAG for German with an RCG-based Parser Developing a TT-MCTAG for German with an RCG-based Parser Laura Kallmeyer, Timm Lichte, Wolfgang Maier, Yannick Parmentier, Johannes Dellert University of Tübingen, Germany CNRS-LORIA, France LREC 2008,

More information

Approaches to control phenomena handout Obligatory control and morphological case: Icelandic and Basque

Approaches to control phenomena handout Obligatory control and morphological case: Icelandic and Basque Approaches to control phenomena handout 6 5.4 Obligatory control and morphological case: Icelandic and Basque Icelandinc quirky case (displaying properties of both structural and inherent case: lexically

More information

Gender and defaults *

Gender and defaults * Gender and defaults * Elena Anagnostopoulou University of Crete 1 Introduction Wurmbrand (2017) argues on the basis of several types of mismatches (gender mismatch nouns, pluralia tantum nouns, and polite

More information

Syntactic types of Russian expressive suffixes

Syntactic types of Russian expressive suffixes Proc. 3rd Northwest Linguistics Conference, Victoria BC CDA, Feb. 17-19, 007 71 Syntactic types of Russian expressive suffixes Olga Steriopolo University of British Columbia olgasteriopolo@hotmail.com

More information

Language Learning and Development. ISSN: (Print) (Online) Journal homepage:

Language Learning and Development. ISSN: (Print) (Online) Journal homepage: Language Learning and Development ISSN: 1547-5441 (Print) 1547-3341 (Online) Journal homepage: http://www.tandfonline.com/loi/hlld20 German children s Use of Word Order and Case Marking to Interpret Simple

More information

A Minimalist Approach to Code-Switching. In the field of linguistics, the topic of bilingualism is a broad one. There are many

A Minimalist Approach to Code-Switching. In the field of linguistics, the topic of bilingualism is a broad one. There are many Schmidt 1 Eric Schmidt Prof. Suzanne Flynn Linguistic Study of Bilingualism December 13, 2013 A Minimalist Approach to Code-Switching In the field of linguistics, the topic of bilingualism is a broad one.

More information

ENGBG1 ENGBL1 Campus Linguistics. Meeting 2. Chapter 7 (Morphology) and chapter 9 (Syntax) Pia Sundqvist

ENGBG1 ENGBL1 Campus Linguistics. Meeting 2. Chapter 7 (Morphology) and chapter 9 (Syntax) Pia Sundqvist Meeting 2 Chapter 7 (Morphology) and chapter 9 (Syntax) Today s agenda Repetition of meeting 1 Mini-lecture on morphology Seminar on chapter 7, worksheet Mini-lecture on syntax Seminar on chapter 9, worksheet

More information

On the Notion Determiner

On the Notion Determiner On the Notion Determiner Frank Van Eynde University of Leuven Proceedings of the 10th International Conference on Head-Driven Phrase Structure Grammar Michigan State University Stefan Müller (Editor) 2003

More information

In Udmurt (Uralic, Russia) possessors bear genitive case except in accusative DPs where they receive ablative case.

In Udmurt (Uralic, Russia) possessors bear genitive case except in accusative DPs where they receive ablative case. Sören E. Worbs The University of Leipzig Modul 04-046-2015 soeren.e.worbs@gmail.de November 22, 2016 Case stacking below the surface: On the possessor case alternation in Udmurt (Assmann et al. 2014) 1

More information

EAGLE: an Error-Annotated Corpus of Beginning Learner German

EAGLE: an Error-Annotated Corpus of Beginning Learner German EAGLE: an Error-Annotated Corpus of Beginning Learner German Adriane Boyd Department of Linguistics The Ohio State University adriane@ling.osu.edu Abstract This paper describes the Error-Annotated German

More information

Enhancing Unlexicalized Parsing Performance using a Wide Coverage Lexicon, Fuzzy Tag-set Mapping, and EM-HMM-based Lexical Probabilities

Enhancing Unlexicalized Parsing Performance using a Wide Coverage Lexicon, Fuzzy Tag-set Mapping, and EM-HMM-based Lexical Probabilities Enhancing Unlexicalized Parsing Performance using a Wide Coverage Lexicon, Fuzzy Tag-set Mapping, and EM-HMM-based Lexical Probabilities Yoav Goldberg Reut Tsarfaty Meni Adler Michael Elhadad Ben Gurion

More information

Context Free Grammars. Many slides from Michael Collins

Context Free Grammars. Many slides from Michael Collins Context Free Grammars Many slides from Michael Collins Overview I An introduction to the parsing problem I Context free grammars I A brief(!) sketch of the syntax of English I Examples of ambiguous structures

More information

Modeling full form lexica for Arabic

Modeling full form lexica for Arabic Modeling full form lexica for Arabic Susanne Alt Amine Akrout Atilf-CNRS Laurent Romary Loria-CNRS Objectives Presentation of the current standardization activity in the domain of lexical data modeling

More information

Construction Grammar. University of Jena.

Construction Grammar. University of Jena. Construction Grammar Holger Diessel University of Jena holger.diessel@uni-jena.de http://www.holger-diessel.de/ Words seem to have a prototype structure; but language does not only consist of words. What

More information

Inflection Classes and Economy

Inflection Classes and Economy Inflection Classes and Economy James P. Blevins (University of Cambridge) 1. Introduction Inflection classes raise a number of basic questions of analysis. Which elements of a morphological system are

More information

Phenomena of gender attraction in Polish *

Phenomena of gender attraction in Polish * Chiara Finocchiaro and Anna Cielicka Phenomena of gender attraction in Polish * 1. Introduction The selection and use of grammatical features - such as gender and number - in producing sentences involve

More information

Words come in categories

Words come in categories Nouns Words come in categories D: A grammatical category is a class of expressions which share a common set of grammatical properties (a.k.a. word class or part of speech). Words come in categories Open

More information

Author: Fatima Lemtouni, Wayzata High School, Wayzata, MN

Author: Fatima Lemtouni, Wayzata High School, Wayzata, MN Title: Do Greetings Reflect Culture? Language: Arabic Author: Fatima Lemtouni, Wayzata High School, Wayzata, MN Level: Beginning/Novice low When: Semester one Theme: How do we greet and introduce each

More information

Syntax Parsing 1. Grammars and parsing 2. Top-down and bottom-up parsing 3. Chart parsers 4. Bottom-up chart parsing 5. The Earley Algorithm

Syntax Parsing 1. Grammars and parsing 2. Top-down and bottom-up parsing 3. Chart parsers 4. Bottom-up chart parsing 5. The Earley Algorithm Syntax Parsing 1. Grammars and parsing 2. Top-down and bottom-up parsing 3. Chart parsers 4. Bottom-up chart parsing 5. The Earley Algorithm syntax: from the Greek syntaxis, meaning setting out together

More information

Grammars & Parsing, Part 1:

Grammars & Parsing, Part 1: Grammars & Parsing, Part 1: Rules, representations, and transformations- oh my! Sentence VP The teacher Verb gave the lecture 2015-02-12 CS 562/662: Natural Language Processing Game plan for today: Review

More information

11/29/2010. Statistical Parsing. Statistical Parsing. Simple PCFG for ATIS English. Syntactic Disambiguation

11/29/2010. Statistical Parsing. Statistical Parsing. Simple PCFG for ATIS English. Syntactic Disambiguation tatistical Parsing (Following slides are modified from Prof. Raymond Mooney s slides.) tatistical Parsing tatistical parsing uses a probabilistic model of syntax in order to assign probabilities to each

More information

UC Berkeley Berkeley Undergraduate Journal of Classics

UC Berkeley Berkeley Undergraduate Journal of Classics UC Berkeley Berkeley Undergraduate Journal of Classics Title The Declension of Bloom: Grammar, Diversion, and Union in Joyce s Ulysses Permalink https://escholarship.org/uc/item/56m627ts Journal Berkeley

More information

MODELING DEPENDENCY GRAMMAR WITH RESTRICTED CONSTRAINTS. Ingo Schröder Wolfgang Menzel Kilian Foth Michael Schulz * Résumé - Abstract

MODELING DEPENDENCY GRAMMAR WITH RESTRICTED CONSTRAINTS. Ingo Schröder Wolfgang Menzel Kilian Foth Michael Schulz * Résumé - Abstract T.A.L., vol. 38, n o 1, pp. 1 30 MODELING DEPENDENCY GRAMMAR WITH RESTRICTED CONSTRAINTS Ingo Schröder Wolfgang Menzel Kilian Foth Michael Schulz * Résumé - Abstract Parsing of dependency grammar has been

More information

Tutorial on Paradigms

Tutorial on Paradigms Jochen Trommer jtrommer@uni-leipzig.de University of Leipzig Institute of Linguistics Workshop on the Division of Labor between Phonology & Morphology January 16, 2009 Textbook Paradigms sg pl Nom dominus

More information

Parsing of part-of-speech tagged Assamese Texts

Parsing of part-of-speech tagged Assamese Texts IJCSI International Journal of Computer Science Issues, Vol. 6, No. 1, 2009 ISSN (Online): 1694-0784 ISSN (Print): 1694-0814 28 Parsing of part-of-speech tagged Assamese Texts Mirzanur Rahman 1, Sufal

More information

Type Theory and Universal Grammar

Type Theory and Universal Grammar Type Theory and Universal Grammar Aarne Ranta Department of Computer Science and Engineering Chalmers University of Technology and Göteborg University Abstract. The paper takes a look at the history of

More information

Accurate Unlexicalized Parsing for Modern Hebrew

Accurate Unlexicalized Parsing for Modern Hebrew Accurate Unlexicalized Parsing for Modern Hebrew Reut Tsarfaty and Khalil Sima an Institute for Logic, Language and Computation, University of Amsterdam Plantage Muidergracht 24, 1018TV Amsterdam, The

More information

Participate in expanded conversations and respond appropriately to a variety of conversational prompts

Participate in expanded conversations and respond appropriately to a variety of conversational prompts Students continue their study of German by further expanding their knowledge of key vocabulary topics and grammar concepts. Students not only begin to comprehend listening and reading passages more fully,

More information

6.863J Natural Language Processing Lecture 12: Featured attraction. Instructor: Robert C. Berwick

6.863J Natural Language Processing Lecture 12: Featured attraction. Instructor: Robert C. Berwick 6.863J Natural Language Processing Lecture 12: Featured attraction Instructor: Robert C. Berwick berwick@ai.mit.edu The Menu Bar Administrivia: 3a due Friday; Lab 3b out Weds; due after vacation Agenda:

More information

Compositional Semantics

Compositional Semantics Compositional Semantics CMSC 723 / LING 723 / INST 725 MARINE CARPUAT marine@cs.umd.edu Words, bag of words Sequences Trees Meaning Representing Meaning An important goal of NLP/AI: convert natural language

More information

cmp-lg/ Jul 1995

cmp-lg/ Jul 1995 A CONSTRAINT-BASED CASE FRAME LEXICON ARCHITECTURE 1 Introduction Kemal Oazer and Okan Ylmaz Department of Computer Engineering and Information Science Bilkent University Bilkent, Ankara 0, Turkey fko,okang@cs.bilkent.edu.tr

More information

Applications of memory-based natural language processing

Applications of memory-based natural language processing Applications of memory-based natural language processing Antal van den Bosch and Roser Morante ILK Research Group Tilburg University Prague, June 24, 2007 Current ILK members Principal investigator: Antal

More information

Interactive Corpus Annotation of Anaphor Using NLP Algorithms

Interactive Corpus Annotation of Anaphor Using NLP Algorithms Interactive Corpus Annotation of Anaphor Using NLP Algorithms Catherine Smith 1 and Matthew Brook O Donnell 1 1. Introduction Pronouns occur with a relatively high frequency in all forms English discourse.

More information

The building blocks of HPSG grammars. Head-Driven Phrase Structure Grammar (HPSG) HPSG grammars from a linguistic perspective

The building blocks of HPSG grammars. Head-Driven Phrase Structure Grammar (HPSG) HPSG grammars from a linguistic perspective Te building blocks of HPSG grammars Head-Driven Prase Structure Grammar (HPSG) In HPSG, sentences, s, prases, and multisentence discourses are all represented as signs = complexes of ponological, syntactic/semantic,

More information

Dreistadt: A language enabled MOO for language learning

Dreistadt: A language enabled MOO for language learning Dreistadt: A language enabled MOO for language learning Till Christopher Lech 1 and Koenraad de Smedt 2 Abstract. Dreistadt is an educational MOO (Multi User Domain, Object Oriented) for language learning.

More information

The presence of interpretable but ungrammatical sentences corresponds to mismatches between interpretive and productive parsing.

The presence of interpretable but ungrammatical sentences corresponds to mismatches between interpretive and productive parsing. Lecture 4: OT Syntax Sources: Kager 1999, Section 8; Legendre et al. 1998; Grimshaw 1997; Barbosa et al. 1998, Introduction; Bresnan 1998; Fanselow et al. 1999; Gibson & Broihier 1998. OT is not a theory

More information

Language Acquisition by Identical vs. Fraternal SLI Twins * Karin Stromswold & Jay I. Rifkin

Language Acquisition by Identical vs. Fraternal SLI Twins * Karin Stromswold & Jay I. Rifkin Stromswold & Rifkin, Language Acquisition by MZ & DZ SLI Twins (SRCLD, 1996) 1 Language Acquisition by Identical vs. Fraternal SLI Twins * Karin Stromswold & Jay I. Rifkin Dept. of Psychology & Ctr. for

More information

Specifying a shallow grammatical for parsing purposes

Specifying a shallow grammatical for parsing purposes Specifying a shallow grammatical for parsing purposes representation Atro Voutilainen and Timo J~irvinen Research Unit for Multilingual Language Technology P.O. Box 4 FIN-0004 University of Helsinki Finland

More information

arxiv:cmp-lg/ v1 7 Jun 1997 Abstract

arxiv:cmp-lg/ v1 7 Jun 1997 Abstract Comparing a Linguistic and a Stochastic Tagger Christer Samuelsson Lucent Technologies Bell Laboratories 600 Mountain Ave, Room 2D-339 Murray Hill, NJ 07974, USA christer@research.bell-labs.com Atro Voutilainen

More information

Citation for published version (APA): Veenstra, M. J. A. (1998). Formalizing the minimalist program Groningen: s.n.

Citation for published version (APA): Veenstra, M. J. A. (1998). Formalizing the minimalist program Groningen: s.n. University of Groningen Formalizing the minimalist program Veenstra, Mettina Jolanda Arnoldina IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF if you wish to cite from

More information

THE VERB ARGUMENT BROWSER

THE VERB ARGUMENT BROWSER THE VERB ARGUMENT BROWSER Bálint Sass sass.balint@itk.ppke.hu Péter Pázmány Catholic University, Budapest, Hungary 11 th International Conference on Text, Speech and Dialog 8-12 September 2008, Brno PREVIEW

More information

INTRODUCTION TO MORPHOLOGY Mark C. Baker and Jonathan David Bobaljik. Rutgers and McGill. Draft 6 INFLECTION

INTRODUCTION TO MORPHOLOGY Mark C. Baker and Jonathan David Bobaljik. Rutgers and McGill. Draft 6 INFLECTION INTRODUCTION TO MORPHOLOGY 2002-2003 Mark C. Baker and Jonathan David Bobaljik Rutgers and McGill Draft 6 INFLECTION Many approaches to morphology, both traditional and generative, draw a distinction between

More information

Constraining X-Bar: Theta Theory

Constraining X-Bar: Theta Theory Constraining X-Bar: Theta Theory Carnie, 2013, chapter 8 Kofi K. Saah 1 Learning objectives Distinguish between thematic relation and theta role. Identify the thematic relations agent, theme, goal, source,

More information

Ensemble Technique Utilization for Indonesian Dependency Parser

Ensemble Technique Utilization for Indonesian Dependency Parser Ensemble Technique Utilization for Indonesian Dependency Parser Arief Rahman Institut Teknologi Bandung Indonesia 23516008@std.stei.itb.ac.id Ayu Purwarianti Institut Teknologi Bandung Indonesia ayu@stei.itb.ac.id

More information

(12) United States Patent Bernth et al.

(12) United States Patent Bernth et al. , (12) United States Patent Bernth et al. US006285978B1 (10) Patent N0.: (45) Date of Patent: Sep. 4, 2001 (54) SYSTEM AND METHOD FOR ESTIMATING ACCURACY OF AN AUTOMATIC NATURAL LANGUAGE TRANSLATION (75)

More information

Chunk Parsing for Base Noun Phrases using Regular Expressions. Let s first let the variable s0 be the sentence tree of the first sentence.

Chunk Parsing for Base Noun Phrases using Regular Expressions. Let s first let the variable s0 be the sentence tree of the first sentence. NLP Lab Session Week 8 October 15, 2014 Noun Phrase Chunking and WordNet in NLTK Getting Started In this lab session, we will work together through a series of small examples using the IDLE window and

More information

AN EXPERIMENTAL APPROACH TO NEW AND OLD INFORMATION IN TURKISH LOCATIVES AND EXISTENTIALS

AN EXPERIMENTAL APPROACH TO NEW AND OLD INFORMATION IN TURKISH LOCATIVES AND EXISTENTIALS AN EXPERIMENTAL APPROACH TO NEW AND OLD INFORMATION IN TURKISH LOCATIVES AND EXISTENTIALS Engin ARIK 1, Pınar ÖZTOP 2, and Esen BÜYÜKSÖKMEN 1 Doguş University, 2 Plymouth University enginarik@enginarik.com

More information

Type-driven semantic interpretation and feature dependencies in R-LFG

Type-driven semantic interpretation and feature dependencies in R-LFG Type-driven semantic interpretation and feature dependencies in R-LFG Mark Johnson Revision of 23rd August, 1997 1 Introduction This paper describes a new formalization of Lexical-Functional Grammar called

More information

Informatics 2A: Language Complexity and the. Inf2A: Chomsky Hierarchy

Informatics 2A: Language Complexity and the. Inf2A: Chomsky Hierarchy Informatics 2A: Language Complexity and the Chomsky Hierarchy September 28, 2010 Starter 1 Is there a finite state machine that recognises all those strings s from the alphabet {a, b} where the difference

More information

A Computational Evaluation of Case-Assignment Algorithms

A Computational Evaluation of Case-Assignment Algorithms A Computational Evaluation of Case-Assignment Algorithms Miles Calabresi Advisors: Bob Frank and Jim Wood Submitted to the faculty of the Department of Linguistics in partial fulfillment of the requirements

More information

Derivational and Inflectional Morphemes in Pak-Pak Language

Derivational and Inflectional Morphemes in Pak-Pak Language Derivational and Inflectional Morphemes in Pak-Pak Language Agustina Situmorang and Tima Mariany Arifin ABSTRACT The objectives of this study are to find out the derivational and inflectional morphemes

More information

Using dialogue context to improve parsing performance in dialogue systems

Using dialogue context to improve parsing performance in dialogue systems Using dialogue context to improve parsing performance in dialogue systems Ivan Meza-Ruiz and Oliver Lemon School of Informatics, Edinburgh University 2 Buccleuch Place, Edinburgh I.V.Meza-Ruiz@sms.ed.ac.uk,

More information

Using a Native Language Reference Grammar as a Language Learning Tool

Using a Native Language Reference Grammar as a Language Learning Tool Using a Native Language Reference Grammar as a Language Learning Tool Stacey I. Oberly University of Arizona & American Indian Language Development Institute Introduction This article is a case study in

More information

International Journal of Informative & Futuristic Research ISSN (Online):

International Journal of Informative & Futuristic Research ISSN (Online): Research Paper Volume 2 Issue 5 January 2015 International Journal of Informative & Futuristic Research ISSN (Online): 2347-1697 Structure Of Manipuri Pronouns Paper ID IJIFR/ V2/ E5/ 041 Page No. 1335-1344

More information

Adapting Stochastic Output for Rule-Based Semantics

Adapting Stochastic Output for Rule-Based Semantics Adapting Stochastic Output for Rule-Based Semantics Wissenschaftliche Arbeit zur Erlangung des Grades eines Diplom-Handelslehrers im Fachbereich Wirtschaftswissenschaften der Universität Konstanz Februar

More information

Derivational: Inflectional: In a fit of rage the soldiers attacked them both that week, but lost the fight.

Derivational: Inflectional: In a fit of rage the soldiers attacked them both that week, but lost the fight. Final Exam (120 points) Click on the yellow balloons below to see the answers I. Short Answer (32pts) 1. (6) The sentence The kinder teachers made sure that the students comprehended the testable material

More information

Morphosyntactic and Referential Cues to the Identification of Generic Statements

Morphosyntactic and Referential Cues to the Identification of Generic Statements Morphosyntactic and Referential Cues to the Identification of Generic Statements Phil Crone pcrone@stanford.edu Department of Linguistics Stanford University Michael C. Frank mcfrank@stanford.edu Department

More information

The Role of the Head in the Interpretation of English Deverbal Compounds

The Role of the Head in the Interpretation of English Deverbal Compounds The Role of the Head in the Interpretation of English Deverbal Compounds Gianina Iordăchioaia i, Lonneke van der Plas ii, Glorianna Jagfeld i (Universität Stuttgart i, University of Malta ii ) Wen wurmt

More information

Aspectual Classes of Verb Phrases

Aspectual Classes of Verb Phrases Aspectual Classes of Verb Phrases Current understanding of verb meanings (from Predicate Logic): verbs combine with their arguments to yield the truth conditions of a sentence. With such an understanding

More information

The History of Language Teaching

The History of Language Teaching The History of Language Teaching Communicative Language Teaching The Early Years Chomsky Important figure in linguistics, but important to language teaching for his destruction of The behaviourist theory

More information

(3) Vocabulary insertion targets subtrees (4) The Superset Principle A vocabulary item A associated with the feature set F can replace a subtree X

(3) Vocabulary insertion targets subtrees (4) The Superset Principle A vocabulary item A associated with the feature set F can replace a subtree X Lexicalizing number and gender in Colonnata Knut Tarald Taraldsen Center for Advanced Study in Theoretical Linguistics University of Tromsø knut.taraldsen@uit.no 1. Introduction Current late insertion

More information

The analysis starts with the phonetic vowel and consonant charts based on the dataset:

The analysis starts with the phonetic vowel and consonant charts based on the dataset: Ling 113 Homework 5: Hebrew Kelli Wiseth February 13, 2014 The analysis starts with the phonetic vowel and consonant charts based on the dataset: a) Given that the underlying representation for all verb

More information

Argument structure and theta roles

Argument structure and theta roles Argument structure and theta roles Introduction to Syntax, EGG Summer School 2017 András Bárány ab155@soas.ac.uk 26 July 2017 Overview Where we left off Arguments and theta roles Some consequences of theta

More information

Control and Boundedness

Control and Boundedness Control and Boundedness Having eliminated rules, we would expect constructions to follow from the lexical categories (of heads and specifiers of syntactic constructions) alone. Combinatory syntax simply

More information

Objectives. Chapter 2: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition

Objectives. Chapter 2: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition Chapter 2: The Representation of Knowledge Expert Systems: Principles and Programming, Fourth Edition Objectives Introduce the study of logic Learn the difference between formal logic and informal logic

More information

Universal Grammar 2. Universal Grammar 1. Forms and functions 1. Universal Grammar 3. Conceptual and surface structure of complex clauses

Universal Grammar 2. Universal Grammar 1. Forms and functions 1. Universal Grammar 3. Conceptual and surface structure of complex clauses Universal Grammar 1 evidence : 1. crosslinguistic investigation of properties of languages 2. evidence from language acquisition 3. general cognitive abilities 1. Properties can be reflected in a.) structural

More information

Formulaic Language and Fluency: ESL Teaching Applications

Formulaic Language and Fluency: ESL Teaching Applications Formulaic Language and Fluency: ESL Teaching Applications Formulaic Language Terminology Formulaic sequence One such item Formulaic language Non-count noun referring to these items Phraseology The study

More information

Introduction, Organization Overview of NLP, Main Issues

Introduction, Organization Overview of NLP, Main Issues HG2051 Language and the Computer Computational Linguistics with Python Introduction, Organization Overview of NLP, Main Issues Francis Bond Division of Linguistics and Multilingual Studies http://www3.ntu.edu.sg/home/fcbond/

More information

Beyond the Pipeline: Discrete Optimization in NLP

Beyond the Pipeline: Discrete Optimization in NLP Beyond the Pipeline: Discrete Optimization in NLP Tomasz Marciniak and Michael Strube EML Research ggmbh Schloss-Wolfsbrunnenweg 33 69118 Heidelberg, Germany http://www.eml-research.de/nlp Abstract We

More information

Specification and Evaluation of Machine Translation Toy Systems - Criteria for laboratory assignments

Specification and Evaluation of Machine Translation Toy Systems - Criteria for laboratory assignments Specification and Evaluation of Machine Translation Toy Systems - Criteria for laboratory assignments Cristina Vertan, Walther v. Hahn University of Hamburg, Natural Language Systems Division Hamburg,

More information

Analysis of Probabilistic Parsing in NLP

Analysis of Probabilistic Parsing in NLP Analysis of Probabilistic Parsing in NLP Krishna Karoo, Dr.Girish Katkar Research Scholar, Department of Electronics & Computer Science, R.T.M. Nagpur University, Nagpur, India Head of Department, Department

More information

Hindi Aspectual Verb Complexes

Hindi Aspectual Verb Complexes Hindi Aspectual Verb Complexes HPSG-09 1 Introduction One of the goals of syntax is to termine how much languages do vary, in the hope to be able to make hypothesis about how much natural languages can

More information

Multiple case assignment and the English pseudo-passive *

Multiple case assignment and the English pseudo-passive * Multiple case assignment and the English pseudo-passive * Norvin Richards Massachusetts Institute of Technology Previous literature on pseudo-passives (see van Riemsdijk 1978, Chomsky 1981, Hornstein &

More information

Basic concepts: words and morphemes. LING 481 Winter 2011

Basic concepts: words and morphemes. LING 481 Winter 2011 Basic concepts: words and morphemes LING 481 Winter 2011 Organization Word diagnostics different senses Morpheme types Allomorphy exercises What is a word? (Much more on difficulties identifying words

More information

Refining the Design of a Contracting Finite-State Dependency Parser

Refining the Design of a Contracting Finite-State Dependency Parser Refining the Design of a Contracting Finite-State Dependency Parser Anssi Yli-Jyrä and Jussi Piitulainen and Atro Voutilainen The Department of Modern Languages PO Box 3 00014 University of Helsinki {anssi.yli-jyra,jussi.piitulainen,atro.voutilainen}@helsinki.fi

More information

BASIC ENGLISH. Book GRAMMAR

BASIC ENGLISH. Book GRAMMAR BASIC ENGLISH Book 1 GRAMMAR Anne Seaton Y. H. Mew Book 1 Three Watson Irvine, CA 92618-2767 Web site: www.sdlback.com First published in the United States by Saddleback Educational Publishing, 3 Watson,

More information

The Acquisition of Person and Number Morphology Within the Verbal Domain in Early Greek

The Acquisition of Person and Number Morphology Within the Verbal Domain in Early Greek Vol. 4 (2012) 15-25 University of Reading ISSN 2040-3461 LANGUAGE STUDIES WORKING PAPERS Editors: C. Ciarlo and D.S. Giannoni The Acquisition of Person and Number Morphology Within the Verbal Domain in

More information

C.A.E. LUSCHNIG ANCIENT GREEK. A Literary Appro a c h. Second Edition Revised by C.A.E. Luschnig and Deborah Mitchell

C.A.E. LUSCHNIG ANCIENT GREEK. A Literary Appro a c h. Second Edition Revised by C.A.E. Luschnig and Deborah Mitchell C.A.E. LUSCHNIG AN INTRODUCTION TO ANCIENT GREEK A Literary Appro a c h Second Edition Revised by C.A.E. Luschnig and Deborah Mitchell AN INTRODUCTION TO ANCIENT GREEK A Literary Approach Second Edition

More information

Modeling Attachment Decisions with a Probabilistic Parser: The Case of Head Final Structures

Modeling Attachment Decisions with a Probabilistic Parser: The Case of Head Final Structures Modeling Attachment Decisions with a Probabilistic Parser: The Case of Head Final Structures Ulrike Baldewein (ulrike@coli.uni-sb.de) Computational Psycholinguistics, Saarland University D-66041 Saarbrücken,

More information

1 The problem with optional syntactic rules in the paraphrasing system of MTT

1 The problem with optional syntactic rules in the paraphrasing system of MTT MTT 2007, Klagenfurt, May 21 24, 2007 Wiener Slawistischer Almanach, Sonderband 69, 2007 Towards a Modified Notation of Support Verbs (Considerations on German material) Robert Zangenfeind CIS / Institute

More information

The Acquisition of English Grammatical Morphemes: A Case of Iranian EFL Learners

The Acquisition of English Grammatical Morphemes: A Case of Iranian EFL Learners 105 By Fatemeh Behjat & Firooz Sadighi The Acquisition of English Grammatical Morphemes: A Case of Iranian EFL Learners Fatemeh Behjat fb_304@yahoo.com Islamic Azad University, Abadeh Branch, Iran Fatemeh

More information

Syntactic Agreement. Roberta D Alessandro 18 November 2015

Syntactic Agreement. Roberta D Alessandro 18 November 2015 Syntactic Agreement Roberta D Alessandro 18 November 2015 1 Syntactic vs Morphological agr. Syntactic vs morphological agreement Do we need morphology to know that Agree has taken place? (1) Jij loopt

More information

"f TOPIC =T COMP COMP... OBJ

f TOPIC =T COMP COMP... OBJ TREATMENT OF LONG DISTANCE DEPENDENCIES IN LFG AND TAG: FUNCTIONAL UNCERTAINTY IN LFG IS A COROLLARY IN TAG" Aravind K. Joshi Dept. of Computer & Information Science University of Pennsylvania Philadelphia,

More information

2014 Colleen Elizabeth Fitzgerald

2014 Colleen Elizabeth Fitzgerald 2014 Colleen Elizabeth Fitzgerald UNIFORMITY OF PRONOUN CASE ERRORS IN TYPICAL DEVELOPMENT: THE ASSOCIATION BETWEEN CHILDREN S FIRST PERSON AND THIRD PERSON CASE ERRORS IN A LONGITUDINAL STUDY BY COLLEEN

More information

Target Language Preposition Selection an Experiment with Transformation-Based Learning and Aligned Bilingual Data

Target Language Preposition Selection an Experiment with Transformation-Based Learning and Aligned Bilingual Data Target Language Preposition Selection an Experiment with Transformation-Based Learning and Aligned Bilingual Data Ebba Gustavii Department of Linguistics and Philology, Uppsala University, Sweden ebbag@stp.ling.uu.se

More information

Some Principles of Automated Natural Language Information Extraction

Some Principles of Automated Natural Language Information Extraction Some Principles of Automated Natural Language Information Extraction Gregers Koch Department of Computer Science, Copenhagen University DIKU, Universitetsparken 1, DK-2100 Copenhagen, Denmark Abstract

More information

Character Stream Parsing of Mixed-lingual Text

Character Stream Parsing of Mixed-lingual Text Character Stream Parsing of Mixed-lingual Text Harald Romsdorfer and Beat Pfister Speech Processing Group Computer Engineering and Networks Laboratory ETH Zurich {romsdorfer,pfister}@tik.ee.ethz.ch Abstract

More information

Semi-supervised methods of text processing, and an application to medical concept extraction. Yacine Jernite Text-as-Data series September 17.

Semi-supervised methods of text processing, and an application to medical concept extraction. Yacine Jernite Text-as-Data series September 17. Semi-supervised methods of text processing, and an application to medical concept extraction Yacine Jernite Text-as-Data series September 17. 2015 What do we want from text? 1. Extract information 2. Link

More information

AQUA: An Ontology-Driven Question Answering System

AQUA: An Ontology-Driven Question Answering System AQUA: An Ontology-Driven Question Answering System Maria Vargas-Vera, Enrico Motta and John Domingue Knowledge Media Institute (KMI) The Open University, Walton Hall, Milton Keynes, MK7 6AA, United Kingdom.

More information

THE MORPHO-PHONOLOGY OF POLISH MASCULINE PERSONAL DECLENSIONS Sławomir Zdziebko

THE MORPHO-PHONOLOGY OF POLISH MASCULINE PERSONAL DECLENSIONS Sławomir Zdziebko GPRT 2013, Budapest THE MORPHO-PHONOLOGY OF POLISH MASCULINE PERSONAL DECLENSIONS Sławomir Zdziebko (s.zdziebko86@gmail.com) 1. The fundamental glitch of Polish palatalizations is that: the same consonants

More information